21 hours ago
Hong Kong, Hong KongSenior
Responsibilities
- Design, develop, and maintain Python-based data analytics applications, pipelines, integrations, and production services.
- Use Java where applicable for existing JVM-based services and integrations.
- Build scalable solutions for high-volume orders, executions, trades, positions, and related financial data.
- Develop analytics tools, dashboards, batch jobs, automated workflows, and data distribution processes.
- Use AI-assisted development tools and contribute to AI-powered monitoring, alerting, and workflow automation agents.
- Implement data ingestion, validation, quality, metadata, lineage, and remediation processes.
- Support production processes and batch jobs during Asia morning hours and coordinate operational handoffs across US and UK teams.
- Participate in monitoring, incident response, root-cause analysis, permanent remediation, operational resilience, and business continuity.
- Gather requirements from business subject-matter experts and quantitative analysts and translate them into reusable technical solutions.
- Partner with Markets Technology teams to support data sharing, analytics, and reporting needs.
Requirements
- 8–10 years of experience in software engineering, data engineering, or data analytics within banking or financial services.
- Strong hands-on experience designing, building, and maintaining production-grade data systems as an individual contributor.
- Strong proficiency in Python and knowledge of Java for JVM-based services is a plus.
- Experience with modern AI-assisted coding and testing tools such as GitHub Copilot, Devin, Claude, or equivalent.
- Practical experience designing or building LLM-powered or agentic solutions for monitoring, alerting, or operational workflows is strongly preferred.
- Strong understanding of Markets financial data, including orders, executions, trade processing, positions, P&L, risk, and reference data; Prime Services or Prime Brokerage experience is a plus.
- Experience working with quantitative analysts, business stakeholders, globally distributed teams, and global production environments.
- Familiarity with Trino or Starburst, S3, Kafka, and Spark is highly preferred.
- Experience with data ingestion and distribution frameworks, distributed messaging, distributed caching, databases, batch processing, workflow orchestration, data quality, and analytics platforms.
- Experience with Gemfire or Redis, SQL, relational and NoSQL database management systems, data lakes, data warehouses, and data visualization platforms.
- Familiarity with CI/CD pipelines, containerization, and deployment automation.
- Bachelor's or university degree or equivalent experience, preferably in Computer Science, Information Systems, Mathematics, Statistics, Engineering, or a related quantitative field.
- Excellent written and verbal communication, diplomacy, facilitation, and ability to explain technical concepts to business and executive audiences.
- A master's degree or advanced certifications in a relevant field is preferred.
Tech Stack
Categories
Data Engineering
About Citi
Citi is a public financial-services company offering consumer and institutional banking, credit cards, wealth management, treasury and trade solutions, and capital-markets services. It serves individuals, corporations, financial institutions, and governments in more than 160 countries and jurisdictions, earning interest and fee income from lending, payments, trading, and advisory. Founded in 1812 and headquartered in New York, it trades on the NYSE under the ticker C.